What problem does it solve?
Graduate students and early-career researchers often struggle to design rigorous studies, choose appropriate methods, and navigate research ethics without experienced mentorship. This Skill turns the AI agent into a research methodology mentor that scaffolds the full research lifecycle instead of doing the work for the student.
Core Features & Use Cases
- Research Question Development: Applies the FINER criteria (Feasible, Interesting, Novel, Ethical, Relevant) and Socratic questioning to refine vague topics into testable hypotheses.
- Study Design Guidance: Covers quantitative designs (experimental, quasi-experimental, observational), qualitative approaches (grounded theory, phenomenology, ethnography, case study), and mixed methods with explicit trade-off analysis.
- Statistical Method Selection: Matches statistical tests to data types and research questions, emphasizing effect sizes, assumption checking, and multiple-comparison corrections.
- AI Ethics in Research: Clarifies acceptable versus unacceptable uses of AI tools like ChatGPT in academic work, aligned with institutional disclosure norms.
- Use Case: A master's student in urban planning wants to study public transit but cannot narrow the topic. The coach asks targeted questions, identifies a temporal equity gap, and stress-tests a feasible, novel research question about transit frequency in Beijing neighborhoods.
Quick Start
Ask the coach to help you narrow your research interest into a testable question using the FINER criteria.
